Modern energy access to all in rural India: An integrated implementation strategy

Expanding energy access to the rural population of India presents a critical challenge for its government. The presence of 364 million people without access to electricity and 726 million who rely on biomass for cooking indicate both the failure of past policies and programs, and the need for a radical redesign of the current system. We propose an integrated implementation framework with recommendations for adopting business principles with innovative institutional, regulatory, financing and delivery mechanisms. The framework entails establishment of rural energy access authorities and energy access funds, both at the national and regional levels, to be empowered with enabling regulatory policies, capital resources and the support of multi-stakeholder partnership. These institutions are expected to design, lead, manage and monitor the rural energy interventions. At the other end, trained entrepreneurs would be expected to establish bioenergy-based micro-enterprises that will produce and distribute energy carriers to rural households at an affordable cost. The ESCOs will function as intermediaries between these enterprises and the international carbon market both in aggregating carbon credits and in trading them under CDM. If implemented, such a program could address the challenges of rural energy empowerment by creating access to modern energy carriers and climate change mitigation. (C) 2011 Elsevier Ltd. All rights reserved.

Air Pollution Control

The air we breathe is being polluted by activities such as vehicles; burning coal, oil, and other fossil fuels; and manufacturing chemicals. Air pollution can even come from smaller, everyday activities such as cooking, space heating, and degreasing and painting operations. These activities add gases and particles to the air we breathe. When these gases and particles accumulate in the air in high enough concentrations, they can harm us and our environment. The module on Air Pollution deals with the various sources of air pollution and the associated environmental and health impacts. It also discusses the appropriate measures to control/prevent the same.

Defluoridation of Drinking Water and Rainwater Harvesting Using a Solar Still

When people drink water having a fluoride (F-) concentration >1-1.5 mg/L for a long period of time, various ailments that are collectively referred to as fluorosis occur. Based on the design of Thomas (http://www.planetkerala.org), an inclined basin-type solar still containing sand and water has been used at Bangalore for defluoridation. For water samples having a fluoride concentration in the range 5-20 mg/L, the fluoride concentration in the distillate was usually <1.5 mg/L. During the periods October 2006 May 2007 and October 2007 May 2008, the volume of distillate showed a significant diurnal variation, ranging from 0.3 to 4.0 L/m(2).day. Based on the figures for 2006, the cost of the still was about Rs. 850 (US$16) for collector areas in the range 0.50-0.57 m(2). The occurrence of F- in the distillate merits further investigation. Overall, the still effectively removes F-, but a large area of the collector, in the range 2.5-25 m(2), is needed to produce about 10 L of distilled water for cooking and drinking. Rainwater falling on the upper surface of the still was collected, and its fluoride concentration was found to be below the desirable limit of 1 mg/L. Hence it can also be used for cooking and drinking.

Prior image-constrained l(1)-norm-based reconstruction method for effective usage of structural information in diffuse optical tomography

A novel approach that can more effectively use the structural information provided by the traditional imaging modalities in multimodal diffuse optical tomographic imaging is introduced. This approach is based on a prior image-constrained-l(1) minimization scheme and has been motivated by the recent progress in the sparse image reconstruction techniques. It is shown that the proposed framework is more effective in terms of localizing the tumor region and recovering the optical property values both in numerical and gelatin phantom cases compared to the traditional methods that use structural information. (C) 2012 Optical Society of America

Minimal residual method provides optimal regularization parameter for diffuse optical tomography

The inverse problem in the diffuse optical tomography is known to be nonlinear, ill-posed, and sometimes under-determined, requiring regularization to obtain meaningful results, with Tikhonov-type regularization being the most popular one. The choice of this regularization parameter dictates the reconstructed optical image quality and is typically chosen empirically or based on prior experience. An automated method for optimal selection of regularization parameter that is based on regularized minimal residual method (MRM) is proposed and is compared with the traditional generalized cross-validation method. The results obtained using numerical and gelatin phantom data indicate that the MRM-based method is capable of providing the optimal regularization parameter. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). DOI: 10.1117/1.JBO.17.10.106015]

Sparse Recovery Methods Hold Promise for Diffuse Optical Tomographic Image Reconstruction

The sparse recovery methods utilize the l(p)-normbased regularization in the estimation problem with 0 <= p <= 1. These methods have a better utility when the number of independent measurements are limited in nature, which is a typical case for diffuse optical tomographic image reconstruction problem. These sparse recovery methods, along with an approximation to utilize the l(0)-norm, have been deployed for the reconstruction of diffuse optical images. Their performancewas compared systematically using both numerical and gelatin phantom cases to show that these methods hold promise in improving the reconstructed image quality.

Performance evaluation of typical approximation algorithms for nonconvex l(p)-minimization in diffuse optical tomography

The sparse estimation methods that utilize the l(p)-norm, with p being between 0 and 1, have shown better utility in providing optimal solutions to the inverse problem in diffuse optical tomography. These l(p)-norm-based regularizations make the optimization function nonconvex, and algorithms that implement l(p)-norm minimization utilize approximations to the original l(p)-norm function. In this work, three such typical methods for implementing the l(p)-norm were considered, namely, iteratively reweighted l(1)-minimization (IRL1), iteratively reweighted least squares (IRLS), and the iteratively thresholding method (ITM). These methods were deployed for performing diffuse optical tomographic image reconstruction, and a systematic comparison with the help of three numerical and gelatin phantom cases was executed. The results indicate that these three methods in the implementation of l(p)-minimization yields similar results, with IRL1 fairing marginally in cases considered here in terms of shape recovery and quantitative accuracy of the reconstructed diffuse optical tomographic images. (C) 2014 Optical Society of America

Model-Resolution-Based Basis Pursuit Deconvolution Improves Diffuse Optical Tomographic Imaging

The image reconstruction problem encountered in diffuse optical tomographic imaging is ill-posed in nature, necessitating the usage of regularization to result in stable solutions. This regularization also results in loss of resolution in the reconstructed images. A frame work, that is attributed by model-resolution, to improve the reconstructed image characteristics using the basis pursuit deconvolution method is proposed here. The proposed method performs this deconvolution as an additional step in the image reconstruction scheme. It is shown, both in numerical and experimental gelatin phantom cases, that the proposed method yields better recovery of the target shapes compared to traditional method, without the loss of quantitativeness of the results.

Achieving universal rural energy access in india: A low carbon pathway

India's energy challenges are three pronged: presence of majority energy poor lacking access to modern energy; need for expanding energy system to bridge this access gap as well as to meet the requirements of fast-growing economy; and the desire to partner with global economies in mitigating the threat of climate change. The presence of 364 million people without access to electricity and 726 million relying on biomass for cooking out of a total rural population of 809 million indicate the seriousness of challenge. In this paper, we discuss an innovative approach to address this challenge, which intends to take advantage of recent global developments and untapped capabilities possessed by India. Intention is to use climate change mitigation imperative as a stimulus and adopt a public-private-partnership-driven ‘business model' with innovative institutional, regulatory, financing, and delivery mechanisms. Some of the innovations are: creation of rural energy access authorities within the government system as leadership institutions; establishment of energy access funds to enable transitions from the regime of "investment/fuel subsidies" to "incentive-linked" delivery of energy services; integration of business principles to facilitate affordable and equitable energy sales and carbon trade; and treatment of entrepreneurs as implementation targets. This proposal targets 100% access to modern energy carriers by 2030 through a judicious mix of conventional and biomass energy systems with an investment of US$35 billion over 20 years. The estimated annual cost of universal energy access is about US$9 billion for a GHG mitigation potential of 213Tg CO2e at an abatement cost of US$41/tCO2e. It is a win-win situation for all stakeholders. Households benefit from modern energy carriers at affordable cost; entrepreneurs run profitable energy enterprises; carbon markets have access to CERs; the government has the satisfaction of securing energy access to rural people; and globally, there is a benefit of climate change mitigation.

Incoherence-based optimal selection of independent measurements in diffuse optical tomography

An optimal measurement selection strategy based on incoherence among rows (corresponding to measurements) of the sensitivity (or weight) matrix for the near infrared diffuse optical tomography is proposed. As incoherence among the measurements can be seen as providing maximum independent information into the estimation of optical properties, this provides high level of optimization required for knowing the independency of a particular measurement on its counterparts. The proposed method was compared with the recently established data-resolution matrix-based approach for optimal choice of independent measurements and shown, using simulated and experimental gelatin phantom data sets, to be superior as it does not require an optimal regularization parameter for providing the same information. (C) 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)

A self-assembling polycationic nanocarrier that exhibits exceptional gene transfection efficiency

The lack of an efficient and safe carrier is a major impediment in the field of gene therapy. Although gelatin (GT), a naturally derived polymer, is widely used in drug delivery applications, it is unable to bind DNA efficiently. In this study, a novel polycationic gene carrier was prepared by conjugation of low molecular weight polyethyleneimine (LPEI) with GT through 4-bromonaphthaleic anhydride as a coupling agent to avoid self crosslinking. Self-assembly of LPEI conjugated GT (GT-LPEI) with plasmid DNA (pDNA) yielded nanoparticles with high gene complexation ability to form similar to 250 nm cylindrical nanoparticles with a zeta potential of similar to 27 mV. GT-LPEI showed exceptionally high transfection efficiency (> 90%) in various mammalian cells including primary stem cells with minimal cytotoxicity. The transfection efficiency of GT-LPEI significantly surpassed that of many commercial reagents. The high gene transfection expression was confirmed in vivo. Thus, GT-LPEI is shown to be a promising nonviral carrier for potential use in gene therapy.

Combined Effect of Cryogel Matrix and Temperature-Reversible Soluble-Insoluble Polymer for the Development of in Vitro Human Liver Tissue

Hepatic cell culture on a three-dimensional (3D) matrix or as a hepatosphere appears to be a promising in vitro biomimetic system for liver tissue engineering applications. In this study, we have combined the concept of a 3D scaffold and a spheroid culture to develop an in vitro model to engineer liver tissue for drug screening. We have evaluated the potential of poly(ethylene glycol)-alginate-gelatin (PAG) cryogel matrix for in vitro culture of human liver cell lines. The synthesized cryogel matrix has a flow rate of 7 mL/min and water uptake capacity of 94% that enables easy nutrient transportation in the in vitro cell culture. Youngs modulus of 2.4 kPa and viscoelastic property determine the soft and elastic nature of synthesized cryogel. Biocompatibility of PAG cryogel was evaluated through MTT assay of HepG2 and Huh-7 cells on matrices. The proliferation and functionality of the liver cells were enhanced by culturing hepatic cells as spheroids (hepatospheres) on the PAG cryogel using temperature-reversible soluble-insoluble polymer, poly(N-isopropylacrylamide) (PNIPAAm). Pore size of the cryogel above 100 mu m modulated spheroid size that can prevent hypoxia condition within the spheroid culture. Both the hepatic cells have shown a significant difference (P < 0.05) in terms of cell number and functionality when cultured with PNIPAAm. After 10 days of culture using 0.05% PNIPAAm, the cell number increased by 11- and 7-fold in case of HepG2 and Huh-7 cells, respectively. Similarly, after 10 days of hepatic spheroids culture on PAG cryogel, the albumin production, urea secretion, and CYP450 activity were significantly higher in case of culture with PNIPAAm. The developed tissue mass on the PAG cryogel in the presence of PNIPAAm possess polarity, which was confirmed using F-actin staining and by presence of intercellular bile canalicular lumen. The developed cryogel matrix supports liver cells proliferation and functionality and therefore can be used for in vitro and in vivo drug testing.